Description |
1 online resource (xii, 163 pages) : illustrations |
Series |
Lecture notes in economics and mathematical systems, 0075-8442 ; 597 |
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Lecture notes in economics and mathematical systems ; 597. 0075-8442
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Contents |
Introduction; Markov Decision Processes and the Total Reward Criterion; Expected Utility Theory for Sequential Decision Making; Capacity Control in a Random Environment; Basic Single Resource Capacity Control Models in Revenue Management; Capacity Control Maximizing Additive Time-Separable Utility; Capacity Control Maximizing Atemporal Utility; An Extension: Capacity Control Under a General Discrete Choice Model of Consumer Behavior; Conclusion |
Summary |
"Traditionally, revenue management models aim at a maximization of expected revenue, i.e. a risk-neutral decision-maker is assumed. During the last few years, however, the consideration of revenue risk has gained more and more attention." "By failing to suggest mechanisms for reducing unfavorable revenue levels, traditional risk-neutral capacity control models fall short of meeting the needs of a risk-averse planner. This is why this book revises the well-known capacity control problem in revenue management from the perspective of a risk-averse decision-maker. Modelling an expected utility maximizing decision maker, the problem is formulated as a risk-sensitive Markov decision process. Special emphasis is put on the existence of structured optimal policies. Numerical examples illustrate the results."--Jacket |
Bibliography |
Includes bibliographical references (pages 151-163) |
Notes |
Print version record |
In |
Springer e-books |
Subject |
Revenue management.
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Operations research.
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Marketing.
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Operations Research
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Marketing
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marketing.
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BUSINESS & ECONOMICS -- Insurance -- Risk Assessment & Management.
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Revenue management.
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Affaires.
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Science économique.
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Economie de l'entreprise.
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Revenue management
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Besliskunde.
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Risicoanalyse.
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Capaciteit.
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Controleleer.
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Form |
Electronic book
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ISBN |
9783540730149 |
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3540730141 |
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9783540730132 |
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3540730133 |
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